Cargando…

Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC

BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A ce...

Descripción completa

Detalles Bibliográficos
Autores principales: Guan, Jiezhong, Xu, Xi, Qiu, Guo, He, Chong, Lu, Xiaoyue, Wang, Kang, Liu, Xinyu, Li, Yuanyuan, Ling, Zihang, Tang, Xuan, Liang, Yujie, Tao, Xiaoan, Cheng, Bin, Yang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329320/
https://www.ncbi.nlm.nih.gov/pubmed/37420300
http://dx.doi.org/10.1186/s13046-023-02734-w
_version_ 1785069992406941696
author Guan, Jiezhong
Xu, Xi
Qiu, Guo
He, Chong
Lu, Xiaoyue
Wang, Kang
Liu, Xinyu
Li, Yuanyuan
Ling, Zihang
Tang, Xuan
Liang, Yujie
Tao, Xiaoan
Cheng, Bin
Yang, Bo
author_facet Guan, Jiezhong
Xu, Xi
Qiu, Guo
He, Chong
Lu, Xiaoyue
Wang, Kang
Liu, Xinyu
Li, Yuanyuan
Ling, Zihang
Tang, Xuan
Liang, Yujie
Tao, Xiaoan
Cheng, Bin
Yang, Bo
author_sort Guan, Jiezhong
collection PubMed
description BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model. RESULTS: Incorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identified PYGL as a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC. CONCLUSION: PYGL was identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02734-w.
format Online
Article
Text
id pubmed-10329320
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-103293202023-07-09 Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC Guan, Jiezhong Xu, Xi Qiu, Guo He, Chong Lu, Xiaoyue Wang, Kang Liu, Xinyu Li, Yuanyuan Ling, Zihang Tang, Xuan Liang, Yujie Tao, Xiaoan Cheng, Bin Yang, Bo J Exp Clin Cancer Res Research BACKGROUND: A growing body of research has revealed the connection of metabolism reprogramming and tumor progression, yet how metabolism reprogramming affects inter-patient heterogeneity and prognosis in head and neck squamous cell carcinoma (HNSCC) still requires further explorations. METHODS: A cellular hierarchy framework based on metabolic properties discrepancy, METArisk, was introduced to re-analyze the cellular composition from bulk transcriptomes of 486 patients through deconvolution utilizing single-cell reference profiles from 25 primary and 8 metastatic HNSCC sample integration of previous studies. Machine learning methods were used to identify the correlations between metabolism-related biomarkers and prognosis. The functions of the genes screened out in tumor progression, metastasis and chemotherapy resistance were validated in vitro by cellular functional experiments and in vivo by xenograft tumor mouse model. RESULTS: Incorporating the cellular hierarchy composition and clinical properties, the METArisk phenotype divided multi-patient cohort into two classes, wherein poor prognosis of METArisk-high subgroup was associated with a particular cluster of malignant cells with significant activity of metabolism reprogramming enriched in metastatic single-cell samples. Subsequent analysis targeted for phenotype differences between the METArisk subgroups identified PYGL as a key metabolism-related biomarker that enhances malignancy and chemotherapy resistance by GSH/ROS/p53 pathway, leading to poor prognosis of HNSCC. CONCLUSION: PYGL was identified as a metabolism-related oncogenic biomarker that promotes HNSCC progression, metastasis and chemotherapy resistance though GSH/ROS/p53 pathway. Our study revealed the cellular hierarchy composition of HNSCC from the cell metabolism reprogramming perspective and may provide new inspirations and therapeutic targets for HNSCC in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-023-02734-w. BioMed Central 2023-07-08 /pmc/articles/PMC10329320/ /pubmed/37420300 http://dx.doi.org/10.1186/s13046-023-02734-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Guan, Jiezhong
Xu, Xi
Qiu, Guo
He, Chong
Lu, Xiaoyue
Wang, Kang
Liu, Xinyu
Li, Yuanyuan
Ling, Zihang
Tang, Xuan
Liang, Yujie
Tao, Xiaoan
Cheng, Bin
Yang, Bo
Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title_full Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title_fullStr Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title_full_unstemmed Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title_short Cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker PYGL as a therapeutic target for HNSCC
title_sort cellular hierarchy framework based on single-cell/multi-patient sample sequencing reveals metabolic biomarker pygl as a therapeutic target for hnscc
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329320/
https://www.ncbi.nlm.nih.gov/pubmed/37420300
http://dx.doi.org/10.1186/s13046-023-02734-w
work_keys_str_mv AT guanjiezhong cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT xuxi cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT qiuguo cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT hechong cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT luxiaoyue cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT wangkang cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT liuxinyu cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT liyuanyuan cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT lingzihang cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT tangxuan cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT liangyujie cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT taoxiaoan cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT chengbin cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc
AT yangbo cellularhierarchyframeworkbasedonsinglecellmultipatientsamplesequencingrevealsmetabolicbiomarkerpyglasatherapeutictargetforhnscc